using key six sigma and lean metrics on agile scrum methodology

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International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 4576-4578 © Research India Publications. http://www.ripublication.com 4576 Using Key Six Sigma and Lean Metrics on Agile Scrum Methodology for Performance Improvement Dr. Thirunadana Sikamani K. Prof & H.O.D, Department of Computer Science & Engineering, St. Peters College of Engineering & Technology, Avadi, Chennai 600 05, India Surend Raj Dharmapal Research Scholar, Department of Computer Science, St. Peter University, Avadi, Chennai 600 05, India. Abstract- In this journal, the principle of using lean and six sigma metrics in agile scrum methodology projects for performance improvement is explained. Six Sigma is a business philosophy focusing on continuous improvement, based on a statistical measure of variability. Scrum is an agile project management methodology that can be used to control software and product development using iterative, incremental practices. Overall lean and six sigma focuses on performance improvement and agile focuses on rapid development. By applying lean and six sigma metrics on scrum models helps to improve the performance quality and quick deliverables to customers. Keywords: Agile, Scrum Methodology, Lean Metrics, Six Sigma metrics, scrum and six sigma INTRODUCTION Lean and Six Sigma metrics on software development focuses on reducing defects, improve the quality of deliverables and time to market. Scrum on another side is an iterative and incremental agile software development methodology for managing software projects or product. Applying the lean and six sigma metrics on agile projects have shown greater improvement in delivering quality products quickly to market. SIX SIGMA KEY METRICS Six Sigma methodologies provide businesses with the tools & metrics to improve the capability of their business processes and starts by asking fundamental questions based around customer requirements. Applying rigorous analysis to all processes in the business, Six Sigma can assess whether customer requirements are being met. Some of the key metrics used to measure current state and base improvements off of in future state in six sigma projects are defined below Defects per Opportunity (DPO) This is the ratio between the number of defects in the process (usually found by sampling) and to the opportunities. Usually complex processes produces may have many opportunities for a defect. Example: If there are 34 defects out of 750 units having 10 opportunities per unit, then DPO=34/750*10=0.045/10=0.0045 Defects per Unit (DPU) DPU is slightly different than DPO. It is defined as the average number of defects per unit. The ratio of defects to unit is the universal measure of quality. Consider 100 test cases to be executed for a project. If 10 of these test cases fail for the first time around, we have a first pass yield of 90%. Let‟s say the 10 fails get reworked and re- tested and 5 pass the second time around; the 5 remaining fails pass on the third attempt. Therefore the summary is 100 passes for 115 test case executed. DPU takes a fundamentally different approach to the traditional measurement of yield. It is simply a ratio of the number of defects over the number of units tested. In the above example, the DPU is 15/100 or 0.15. There are 100 units which were found to have a cumulative total of 15 defects when tested. Defects per Million Opportunities (DPMO) Defects per million opportunities (DPMO) is the average number of defects per unit observed during an average production run divided by the number of opportunities to make a defect on the product under study during that run normalized to one million. To convert DPU to DPMO, the calculation step is actually DPU/(opportunities/unit) * 1,000,000. Rolled Throughput Yield (RTY) Rolled Throughput Yield (RTY) is the probability that a single unit can pass through a series of process steps free of defects. For example Functionality 1 having 100 test cases in and 90 out functionality 2 = 90 in and 80 out functionality 3 = 80 in and 75 out functionality = 75 in and 70 out. Functionality 1 = 100 test cases, 10 failed and 5 re-tested to get the 90. The calculation becomes [100-(10+5)]/100 = 85/100 =.85. This is the true yield when you consider rework and scrap. Functionality 2 = 90 test cases in, 10 failed and 7 re-tested to get the 80. [90-(10+7)]/90 =.81 Functionality 3 = 80 test cases in, 5 failed and 3 re-tested to get the 75. [80-(5+3)]/80 =.9 Functionality 4 = 75 test cases in, 5 failed and 10 re-tested to

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Page 1: Using Key Six Sigma and Lean Metrics on Agile Scrum Methodology

International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 4576-4578

© Research India Publications. http://www.ripublication.com

4576

Using Key Six Sigma and Lean Metrics on Agile Scrum Methodology for

Performance Improvement

Dr. Thirunadana Sikamani K.

Prof & H.O.D, Department of Computer Science & Engineering, St. Peter‟ s College of Engineering & Technology, Avadi, Chennai 600 05, India

Surend Raj Dharmapal

Research Scholar, Department of Computer Science, St. Peter University, Avadi, Chennai 600 05, India.

Abstract-

In this journal, the principle of using lean and six sigma

metrics in agile scrum methodology projects for performance

improvement is explained. Six Sigma is a business philosophy

focusing on continuous improvement, based on a statistical

measure of variability. Scrum is an agile project management

methodology that can be used to control software and product

development using iterative, incremental practices. Overall

lean and six sigma focuses on performance improvement and agile focuses on rapid development. By applying lean and six

sigma metrics on scrum models helps to improve the

performance quality and quick deliverables to customers.

Keywords: Agile, Scrum Methodology, Lean Metrics, Six

Sigma metrics, scrum and six sigma

INTRODUCTION

Lean and Six Sigma metrics on software development focuses

on reducing defects, improve the quality of deliverables and time to market. Scrum on another side is an iterative and

incremental agile software development methodology for

managing software projects or product. Applying the lean and

six sigma metrics on agile projects have shown greater

improvement in delivering quality products quickly to market.

SIX SIGMA KEY METRICS

Six Sigma methodologies provide businesses with the tools & metrics to improve the capability of their business processes

and starts by asking fundamental questions based around

customer requirements. Applying rigorous analysis to all

processes in the business, Six Sigma can assess whether

customer requirements are being met. Some of the key metrics

used to measure current state and base improvements off of in

future state in six sigma projects are defined below

Defects per Opportunity (DPO)

This is the ratio between the number of defects in the process

(usually found by sampling) and to the opportunities. Usually

complex processes produces may have many opportunities for

a defect.

Example:

If there are 34 defects out of 750 units having 10 opportunities

per unit, then DPO=34/750*10=0.045/10=0.0045

Defects per Unit (DPU)

DPU is slightly different than DPO. It is defined as the

average number of defects per unit. The ratio of defects to unit

is the universal measure of quality.

Consider 100 test cases to be executed for a project. If 10 of these test cases fail for the first time around, we have a first

pass yield of 90%. Let‟s say the 10 fails get reworked and re-

tested and 5 pass the second time around; the 5 remaining fails

pass on the third attempt. Therefore the summary is 100

passes for 115 test case executed. DPU takes a fundamentally

different approach to the traditional measurement of yield. It

is simply a ratio of the number of defects over the number of

units tested. In the above example, the DPU is 15/100 or 0.15. There are 100 units which were found to have a cumulative

total of 15 defects when tested.

Defects per Million Opportunities (DPMO)

Defects per million opportunities (DPMO) is the average

number of defects per unit observed during an average

production run divided by the number of opportunities to

make a defect on the product under study during that run normalized to one million.

To convert DPU to DPMO, the calculation step is actually

DPU/(opportunities/unit) * 1,000,000.

Rolled Throughput Yield (RTY)

Rolled Throughput Yield (RTY) is the probability that a

single unit can pass through a series of process steps free of

defects.

For example

Functionality 1 having 100 test cases in and 90 out

functionality 2 = 90 in and 80 out functionality 3 = 80 in and

75 out functionality = 75 in and 70 out.

Functionality 1 = 100 test cases, 10 failed and 5 re-tested to

get the 90. The calculation becomes [100-(10+5)]/100 =

85/100 =.85. This is the true yield when you consider rework and scrap.

Functionality 2 = 90 test cases in, 10 failed and 7 re-tested to

get the 80. [90-(10+7)]/90 =.81

Functionality 3 = 80 test cases in, 5 failed and 3 re-tested to

get the 75. [80-(5+3)]/80 =.9

Functionality 4 = 75 test cases in, 5 failed and 10 re-tested to

Page 2: Using Key Six Sigma and Lean Metrics on Agile Scrum Methodology

International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 4576-4578

© Research India Publications. http://www.ripublication.com

4577

get the 70. [75-(5+10)]/75 =.8

Now the true Rolled Throughput Yield is derived as follows

.85*.81*.9*.8 =.49572 or Rounded to the nearest digit, 50%

yield.

Lean Key Metrics

Lean development can be summarized by seven principles,

very close in concept to lean manufacturing principles:

Eliminate waste

Amplify learning

Decide as late as possible

Deliver as fast as possible

Empower the team

Build integrity

See the whole

Wastage Ratio

The number of hours the team members is idle waiting for any

request or any rework hours to the total number of hours. For

example if the total hours consumed in a project is 100 and if

the team is idle for 10 hours. The wastage ratio is.1. The goal of this metric is to bring the wastage ratio to 0. This metric

works based on the principle to eliminate waste in the project.

Recurring defects

The defect root cause analysis is one of the important

processes in software development. The root cause analysis

and learning‟s provide the team the learning opportunity and

to avoid the repetitive mistake in future. This metrics is defined by the number of repetitive

defects/mistake. The definition of repetitive defect/mistake

indicates the defects is already analysed for root cause and

learning was provided to the team. The goal of this metric is

bring the recurring defects to 0. This metric works based on

the principle of amplifying learning and empowering team.

Gained Effort This metrics is used to track the number of hours gained by

delivering the product as early or before the timeline. This can

be derived by subtracting the planned hours by the consumed

hours to complete a project. The goal of this metric is to keep

the results always on positive number. If this metrics gives

negative results, it indicates that we are lagging the scheduled

hours. This metric works based on the principle of delivering

as fast as possible.

INTRODUCTION TO AGILE – SCRUM

METHODOLOGY

Agile SCRUM methodology recommends an empirical

approach to software development, with prototypes, short

delivery cycles and maximal client involvement; to ensure

alignment of deliverables with clients‟ needs. This

methodology also provides benefits of reducing product costs and increasing revenues. The important processes on scrum

are

Product backlog

This is a list of potential software features or requirements for

developers to work on, prioritized by value and risk. A

product owner works with customers and developers to

consider the next increments to deliver to increase

functionality or performance of the software, or to reduce any

significant risks.

Sprint This is set time period (e.g., 30 days) in which the

development team focuses on a set list of goals, or features.

Before beginning a new sprint, the team assesses its current

availability and past work habits using data and discipline

connected with prior sprints to decide how much work they

can pull from the product backlog into a list of features to be

implemented during the current sprint (known as the sprint

backlog). Central to this sprint planning is setting up

conditions where team members can focus and work to their

highest quality standards, without heroics, burnout, or risk of

defects and waste. This is a WIP control mechanism, because

it is used to pull work into the process at the sustainable rate at which it can be done well.

Daily stand-up

A daily stand-up meeting is held to bring to the surface issues

and obstacles using three check-in questions:

1. What‟s been done since the last meeting?

2. What are the team‟s plans until the next meeting?

3. Are any obstacles anticipated before the next

meeting?

The meeting is meant to be short and to the point. Because these open meetings are held so regularly, they provide a

powerful transparency and foster learning and adaptation.

With Scrum, risk and gaps connected with work completion

or performance cannot hide. Whatever is going on, good or

bad, will come into view in real time.

Features delivered

At the end of each sprint, the team delivers tested features,

sometimes completing a customer project. In other cases the

team delivers features that will increase the strength of an

emerging product. Done well, Scrum provides insurance

against losses if a project is cancelled, as the increments delivered tend to stand on their own and may have value in

other projects.

LEAN AND SIX SIGMA METRICS IN AGILE-SCRUM

METHODOLOGY

Below tabular column shows the important six sigma tools

that can be integrated in agile scrum methodology.

Metrics

Source

Metrics Usage in Agile

Six

Sigma

Defects per

Opportunity

(DPO) and

Defects per

Million

Opportunities

In Agile, the defects found in a

sprint give the defects per

opportunity. If there are „n‟

numbers of sprint planned for a

project, multiplying the defects

found in a sprint with „n‟ gives the

probability of defects to occur in

„n‟ number of sprints. The scrum

Page 3: Using Key Six Sigma and Lean Metrics on Agile Scrum Methodology

International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 4576-4578

© Research India Publications. http://www.ripublication.com

4578

master could actually plan to

minimise the defects that could

probably occur in upcoming sprints.

Six

Sigma

Defects per Unit

(DPU)

The defects found in a story could

be defined as the defects per unit.

The number of defects could actually vary based on the size of

story which is defined by story

points. The more the story points,

the probability of defects could be

more.

Six

Sigma

Rolled

Throughput

Yield

The probability of success in a

sprint can be determined using this

metrics. If there are many stories defined, the throughput yield is

arrived by tracking the number of

story points is getting done and the

rework caused due to defects. The

goal of the scrum master is to gain

the rolled throughput yield as much

as possible.

Lean Wastage Ratio The number of hours wasted in a

sprint is calculated by the rework hours and idle hours consumed by

the team members. The ratio is

derived using the wastage hours to

the total hours planned. The goal of

this metric is to bring the wastage

ratio to 0

Lean Recurring

Defects

Retrospective is an important phase

in agile scrum methodology. The

retrospective provide an opportunity to defect root cause

analysis and amplify learning to the

team. The value of this root cause

analysis and learning is measured

by the applicability in the upcoming

sprints. This metrics is used to track

the recurring defects in the sprint

which has root cause already analysed by the team.

Lean Gained Effort This metrics is used to track the

story points or hours gained in each

sprint. This is derived by

subtracting the hours planned to the

hours actually consumed to deliver

the product before the end of sprint.

The results should be always positive.

CONCLUSIONS

Lean & Six Sigma has proven its respective value by applying

its principle in different industries. In software industry, agile

scrum provides improved time-to-market, high collaboration

and customer satisfaction. By applying the Six Sigma and

Lean principles, it provides better process controls, higher

efficiency and effectiveness. Applying customized Six Sigma and Lean metrics in Agile Scrum model help to identify and

resolve defects as early as possible and efficiently.

REFERENCES

[1] Michael L. George, John Maxey, David T.

Rowlands, Malcolm Upton, “The Lean Six Sigma

Pocket Toolbook: A Quick Reference Guide to 70

Tools for Improving Quality and Speed”, 2004 [2] T. M. Kubiak, The Certified Six Sigma Master Black

Belt Handbook, 2012

[3] Craig Larman, Practices For Scaling Lean And

Agile, 2010

[4] Alan Shalloway, Guy Beaver, James R. Trott, Lean-

Agile Software Development: Achieving Enterprise

Agility, 2009

[5] Michele Sliger, Stacia Broderick, The Software

Project Manager's Bridge to Agility, 2008

[6] Mary Poppendieck, Tom Poppendieck, Lean

Software Development: An Agile Toolkit, 2003

[7] Mary Poppendieck and Tom Poppendieck., Scaling Lean & Agile Development: Thinking and

Organizational Tools for Large-Scale Scrum, 2008

[8] Addison-Wesley, Boston, Lean software

development: an agile toolkit. 2003.

[9] James M Morgan and Jeffrey K. Liker. The Toyota

product development system: integrating people,

process, and technology. Productivity Press, New

York, 2006.

[10] Mary Poppendieck and Tom Poppendieck. Leading

lean software development: results are not the point.

Addison-Wesley, Upper Saddle River, NJ, 2010. [11] Forman, G. 2003. An extensive empirical study of

feature selection metrics for text classification. J.

Mach. Learn. Res. 3 (Mar. 2003), 1289-1305.

[12] Fröhlich, B. and Plate, J. The cubic mouse: a new

device for three-dimensional input. In Proceedings of

the SIGCHI Conference on Human Factors in

Computing Systems. 2000.

[13] Bowman, M., Debray, S. K., and Peterson, L. L.

Reasoning about naming systems.. 1993.